EXPLORATORY DATA ANALYSIS (EDA) AND DATA PREPROCESSING

USING CLUSTER & SAMPLING TO ADDRESS IMBALANCED CLASS WITHIN THE DATASET

SOME MORE DATA EXPLORATION AND VISUALIZATION OF RESAMPLED_DATA TO BE USED FOR TRAINING AND TESTING

FEATURE SELECTION PROCESSING

DECISION TREE CLASSIFER

GridSearch Cross Validation

RANDOM FOREST MODEL

TO CHECK THE FEATURE IMPORTANCES IN THE RANDOM FOREST

Gradient Boosting Classifier

NEURAL NETWORK CLASSIFIER TRIALS

GRAPHICAL COMPARISON BETWEEN ROC_AUC AND ACCURACY OF THE THREE MODELS